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Record W2099268113 · doi:10.1890/13-2334.1

EcoVeg: a new approach to vegetation description and classification

2014· article· en· W2099268113 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEcological Monographs · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsMinistère des Ressources naturelles et des Forêts (Québec)Parks CanadaGovernment of British Columbia
Fundersnot available
KeywordsVegetation (pathology)EcologyGeographyFloristicsVegetation classificationEdaphicContext (archaeology)Landscape ecologyPhysiognomySpecies richnessHabitatBiology

Abstract

fetched live from OpenAlex

A vegetation classification approach is needed that can describe the diversity of terrestrial ecosystems and their transformations over large time frames, span the full range of spatial and geographic scales across the globe, and provide knowledge of reference conditions and current states of ecosystems required to make decisions about conservation and resource management. We summarize the scientific basis for EcoVeg, a physiognomic‐floristic‐ecological classification approach that applies to existing vegetation, both cultural (planted and dominated by human processes) and natural (spontaneously formed and dominated by nonhuman ecological processes). The classification is based on a set of vegetation criteria, including physiognomy (growth forms, structure) and floristics (compositional similarity and characteristic species combinations), in conjunction with ecological characteristics, including site factors, disturbance, bioclimate, and biogeography. For natural vegetation, the rationale for the upper levels (formation types) is based on the relation between global‐scale vegetation patterns and macroclimate, hydrology, and substrate. The rationale for the middle levels is based on scaling from regional formations (divisions) to regional floristic‐physiognomic types (macrogroup and group) that respond to meso‐scale biogeographic, climatic, disturbance, and site factors. Finally, the lower levels (alliance and association) are defined by detailed floristic composition that responds to local to regional topo‐edaphic and disturbance gradients. For cultural vegetation, the rationale is similar, but types are based on distinctive vegetation physiognomy and floristics that reflect human activities. The hierarchy provides a structure that organizes regional/continental vegetation patterns in the context of global patterns. A formal nomenclature is provided, along with a descriptive template that provides the differentiating criteria for each type at all levels of the hierarchy. Formation types have been described for the globe; divisions and macrogroups for North America, Latin America and Africa; groups, alliances and associations for the United States, parts of Canada, Latin America and, in partnership with other classifications that share these levels, many other parts of the globe.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.236
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it